[R] running crossvalidation many times MSE for Lasso regression

[Martin Maechler]

>>>>> Jin Li 
>>>>>     on Mon, 23 Oct 2023 15:42:14 +1100 writes:

    > If you are interested in other validation methods (e.g., LOO or n-fold)
    > with more predictive accuracy measures, the function, glmnetcv, in the spm2
    > package can be directly used, and some reproducible examples are
    > also available in ?glmnetcv.

... and once you open that can of w..:   the  glmnet package itself
contains a function  cv.glmnet()  which we (our students) use when teaching.

What's the advantage of the spm2 package ?
At least, the glmnet package is authored by the same who originated and
first published (as in "peer reviewed" ..) these algorithms.



    > On Mon, Oct 23, 2023 at 10:59 AM Duncan Murdoch <murdoch.duncan using gmail.com>
    > wrote:

    >> On 22/10/2023 7:01 p.m., Bert Gunter wrote:
    >> > No error message shown Please include the error message so that it is
    >> > not necessary to rerun your code. This might enable someone to see the
    >> > problem without running the code (e.g. downloading packages, etc.)
    >> 
    >> And it's not necessarily true that someone else would see the same error
    >> message.
    >> 
    >> Duncan Murdoch
    >> 
    >> >
    >> > -- Bert
    >> >
    >> > On Sun, Oct 22, 2023 at 1:36 PM varin sacha via R-help
    >> > <r-help using r-project.org> wrote:
    >> >>
    >> >> Dear R-experts,
    >> >>
    >> >> Here below my R code with an error message. Can somebody help me to fix
    >> this error?
    >> >> Really appreciate your help.
    >> >>
    >> >> Best,
    >> >>
    >> >> ############################################################
    >> >> # MSE CROSSVALIDATION Lasso regression
    >> >>
    >> >> library(glmnet)
    >> >>
    >> >>
    >> >>
    >> x1=c(34,35,12,13,15,37,65,45,47,67,87,45,46,39,87,98,67,51,10,30,65,34,57,68,98,86,45,65,34,78,98,123,202,231,154,21,34,26,56,78,99,83,46,58,91)
    >> >>
    >> x2=c(1,3,2,4,5,6,7,3,8,9,10,11,12,1,3,4,2,3,4,5,4,6,8,7,9,4,3,6,7,9,8,4,7,6,1,3,2,5,6,8,7,1,1,2,9)
    >> >>
    >> y=c(2,6,5,4,6,7,8,10,11,2,3,1,3,5,4,6,5,3.4,5.6,-2.4,-5.4,5,3,6,5,-3,-5,3,2,-1,-8,5,8,6,9,4,5,-3,-7,-9,-9,8,7,1,2)
    >> >> T=data.frame(y,x1,x2)
    >> >>
    >> >> z=matrix(c(x1,x2), ncol=2)
    >> >> cv_model=glmnet(z,y,alpha=1)
    >> >> best_lambda=cv_model$lambda.min
    >> >> best_lambda
    >> >>
    >> >>
    >> >> # Create a list to store the results
    >> >> lst<-list()
    >> >>
    >> >> # This statement does the repetitions (looping)
    >> >> for(i in 1 :1000) {
    >> >>
    >> >> n=45
    >> >>
    >> >> p=0.667
    >> >>
    >> >> sam=sample(1 :n,floor(p*n),replace=FALSE)
    >> >>
    >> >> Training =T [sam,]
    >> >> Testing = T [-sam,]
    >> >>
    >> >> test1=matrix(c(Testing$x1,Testing$x2),ncol=2)
    >> >>
    >> >> predictLasso=predict(cv_model, newx=test1)
    >> >>
    >> >>
    >> >> ypred=predict(predictLasso,newdata=test1)
    >> >> y=T[-sam,]$y
    >> >>
    >> >> MSE = mean((y-ypred)^2)
    >> >> MSE
    >> >> lst[i]<-MSE
    >> >> }
    >> >> mean(unlist(lst))
    >> >> ##################################################################
    >> >>
    >> >>
    >> >>
    >> >>
    >> >> ______________________________________________
    >> >> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
    >> >> https://stat.ethz.ch/mailman/listinfo/r-help
    >> >> PLEASE do read the posting guide
    >> http://www.R-project.org/posting-guide.html
    >> >> and provide commented, minimal, self-contained, reproducible code.
    >> >
    >> > ______________________________________________
    >> > R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
    >> > https://stat.ethz.ch/mailman/listinfo/r-help
    >> > PLEASE do read the posting guide
    >> http://www.R-project.org/posting-guide.html
    >> > and provide commented, minimal, self-contained, reproducible code.
    >> 
    >> ______________________________________________
    >> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
    >> https://stat.ethz.ch/mailman/listinfo/r-help
    >> PLEASE do read the posting guide
    >> http://www.R-project.org/posting-guide.html
    >> and provide commented, minimal, self-contained, reproducible code.
    >> 


    > -- 
    > Jin
    > ------------------------------------------
    > Jin Li, PhD
    > Founder, Data2action, Australia
    > https://www.researchgate.net/profile/Jin_Li32
    > https://scholar.google.com/citations?user=Jeot53EAAAAJ&hl=en

    > [[alternative HTML version deleted]]

    > ______________________________________________
    > R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
    > https://stat.ethz.ch/mailman/listinfo/r-help
    > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
    > and provide commented, minimal, self-contained, reproducible code.